|
| | | | |
| | | |
| Stat |
Members: 3645
Articles: 2'501'711
Articles rated: 2609
20 April 2024 |
|
| | | | |
|
Article overview
| |
|
|
Variational Multi-Task MRI Reconstruction: Joint Reconstruction, Registration and Super-Resolution | | Veronica Corona
; Angelica I. Aviles-Rivero
; Noémie Debroux
; Carole Le Guyader
; Carola-Bibiane Schönlieb
; | | Date: |
16 Aug 2019 | | Abstract: | Motion degradation is a central problem in Magnetic Resonance Imaging (MRI).
This work addresses the problem of how to obtain higher quality, super-resolved
motion-free, reconstructions from highly undersampled MRI data. In this work,
we present for the first time a variational multi-task framework that allows
joining three relevant tasks in MRI: reconstruction, registration and
super-resolution. Our framework takes a set of multiple undersampled MR
acquisitions corrupted by motion into a novel multi-task optimisation model,
which is composed of an $L^2$ fidelity term that allows sharing representation
between tasks, super-resolution foundations and hyperelastic deformations to
model biological tissue behaviors. We demonstrate that this combination yields
to significant improvements over sequential models and other bi-task methods.
Our results exhibit fine details and compensate for motion producing sharp and
highly textured images compared to state of the art methods. | | Source: | arXiv, 1908.5911 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
browser Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
|
| |
|
|
|
|
News, job offers and information for researchers and scientists:
| |
REGISTER